Grazing Incidence X-ray Topographic Studies of Threading Dislocations in Hydrothermal Grown ZnO Single Crystal Substrate
- PDF / 398,901 Bytes
- 6 Pages / 432 x 648 pts Page_size
- 30 Downloads / 208 Views
Grazing Incidence X-ray Topographic Studies of Threading Dislocations in Hydrothermal Grown ZnO Single Crystal Substrates Tianyi Zhou1, Balaji Raghothamachar1, Fangzhen Wu1, and Michael Dudley1,a 1
Department of Materials Science and Engineering, Stony Brook University, Stony Brook, New York, 11794, USA a [email protected] ABSTRACT ZnO single crystal substrates grown by the hydrothermal method have been characterized by grazing incidence X-ray topography using both monochromatic and white synchrotron X-ray beams. 1124 reflection was recorded from the (0001) wafers and the different contrast patterns produced by different threading defects were noted. To uniquely identify the Burgers vectors of these threading dislocation defects, we use ray tracing simulation to compare with observed defect contrast. Our studies showed that threading screw dislocations are not commonly observed. Most threading edge dislocations have the Burgers vector of 1⁄3 [2110] or 1⁄3 [1210]and a density of 2.88×104/cm2. INTRODUCTION Zinc oxide is a promising semiconductor with many desirable properties, such as wide band gap (3.37 eV) and a large exciton banding energy (60 meV) at room temperature [1,2], which make it highly suitable for application in emitter devices in the blue to ultraviolet region and as a substrate material for GaN-based devices. The hydrothermal method is the prevalent technique for growing wurtzite ZnO single crystals [3,4]. The presence of structural defects will strongly influence the performance, lifetime and reliability of devices grown on these substrates. Different dislocation defect types will affect devices to different extents [5] and therefore it is necessary to carry out detailed characterization of all dislocation types. X-ray topography is a powerful technique to image defects in single crystalline materials of low defect densities (
Data Loading...
